The concept of affordances in user interaction design has been around for a long time, but there has always been some confusion as to the meaning of the term and how it applies in various design situations. In this paper, I have attempted to distinguish different kinds of affordances:
Abstract: In reaction to Norman's (1999) essay on misuse of the term affordance in human-computer interaction literature, this article is a concept paper affirming the importance of this powerful concept, reinforcing Norman's distinctions of terminology, and expanding on the usefulness of the concepts in terms of their application to interaction design and evaluation. We define and use four complementary types of affordance in the context of interaction design and evaluation: cognitive affordance, physical affordance, sensory affordance, and functional affordance. The terms cognitive affordance (Norman's perceived affordance) and physical affordance (Norman's real affordance) refer to parallel and equally important usability concepts for interaction design, to which sensory affordance plays a supporting role. We argue that the concept of physical affordance carries a mandatory component of utility or purposeful action (functional affordance). Finally, we provide guidelines to help designers think about how these four kinds of affordance work together naturally in contextualized HCI design or evaluation.
Practitioners and researchers alike need to know how well a given Usability
Evaluation Method (UEM) performs in a given situation and with respect to specific
criteria. Thus, developers of UEMs have an obligation to perform summative,
often comparative, studies to support performance claims with data. Since we
have done our share of UEM development over the years, we have also done many
such studies. The quality of studies to evaluate and compare UEMS has been the
subject of much discussion in the literature, the paper by Gray and Salzman
being the primary example:
Gray, W. D., & Salzman, M. C. (1998). Damaged merchandise? A review of experiments
that compare usability evaluation methods. Human-Computer Interaction, 13
(3), 203-261.
As a by-product of our work and our own experience in doing these studies, we have added our input to this discussion in this paper:
Abstract: The current variety of alternative approaches to usability evaluation methods (UEMs) designed to assess and improve usability in software systems is offset by a general lack of understanding of the capabilities and limitations of each. Practitioners need to know which methods are more effective and in what ways and for what purposes. However, UEMs cannot be evaluated and compared reliably because of the lack of standard criteria for comparison. In this article, we present a practical discussion of factors, comparison criteria, and UEM performance measures useful in studies comparing UEMs. In demonstrating the importance of developing appropriate UEM evaluation criteria, we offer operational definitions and possible measures of UEM performance. We highlight specific challenges that researchers and practitioners face in comparing UEMs and provide a point of departure for further discussion and refinement of the principles and techniques used to approach UEM evaluation and comparison.
Lab-based formative usability evaluation has long been a key means for iteratively achieving and improving usability in user interaction designs. However, sometimes limited ecological validity or difficulties in getting participants into the lab leads developers to seek remote usability evaluation methods. These methods can reveal usability problems occurring with real users doing real day-to-day tasks in real post-deployment working environments.
Our work on remote usability evaluation methods began with Jose Castillo's Masters thesis: The User-Reported Critical Method for Remote Usability Evaluation.
An evaluation study and summary of that work is in:
Abstract: Although existing lab-based formative evaluation is frequently and effectively applied to improving usability of software user interfaces, it has limitations that have led to the concept of remote usability evaluation. Perhaps the most significant impetus for remote usability evaluation methods is the need for a project team to continue formative evaluation downstream, after deployment. The usual kinds of alpha and beta testing do not qualify as formative usability evaluation because they do not yield detailed data observed during usage and associated closely with specific task performance. Critical incident identification is arguably the single most important source of this kind of data. Consequently, we developed and evaluated a cost-effective remote usability evaluation method, based on real users self-reporting critical incidents encountered in real tasks performed in their normal working environments. Results show that users with only brief training can identify, report, and rate the severity level of their own critical incidents.
We no longer work in this area, but our final statement of this work appears in these two Technical Reports:
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